6 results on '"Hautman, C"'
Search Results
2. Combined HIV-1 sequence and integration site analysis informs viral dynamics and allows reconstruction of replicating viral ancestors.
- Author
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Patro SC, Brandt LD, Bale MJ, Halvas EK, Joseph KW, Shao W, Wu X, Guo S, Murrell B, Wiegand A, Spindler J, Raley C, Hautman C, Sobolewski M, Fennessey CM, Hu WS, Luke B, Hasson JM, Niyongabo A, Capoferri AA, Keele BF, Milush J, Hoh R, Deeks SG, Maldarelli F, Hughes SH, Coffin JM, Rausch JW, Mellors JW, and Kearney MF
- Subjects
- Anti-Retroviral Agents therapeutic use, Base Sequence, Cell Line, DNA, Viral genetics, Drug Resistance, Viral, HIV Infections virology, Humans, Leukocytes, Mononuclear virology, Lymph Nodes virology, Mutation, Proviruses genetics, Virus Integration physiology, HIV-1 genetics, Virus Integration genetics, Virus Replication genetics
- Abstract
Understanding HIV-1 persistence despite antiretroviral therapy (ART) is of paramount importance. Both single-genome sequencing (SGS) and integration site analysis (ISA) provide useful information regarding the structure of persistent HIV DNA populations; however, until recently, there was no way to link integration sites to their cognate proviral sequences. Here, we used multiple-displacement amplification (MDA) of cellular DNA diluted to a proviral endpoint to obtain full-length proviral sequences and their corresponding sites of integration. We applied this method to lymph node and peripheral blood mononuclear cells from 5 ART-treated donors to determine whether groups of identical subgenomic sequences in the 2 compartments are the result of clonal expansion of infected cells or a viral genetic bottleneck. We found that identical proviral sequences can result from both cellular expansion and viral genetic bottlenecks occurring prior to ART initiation and following ART failure. We identified an expanded T cell clone carrying an intact provirus that matched a variant previously detected by viral outgrowth assays and expanded clones with wild-type and drug-resistant defective proviruses. We also found 2 clones from 1 donor that carried identical proviruses except for nonoverlapping deletions, from which we could infer the sequence of the intact parental virus. Thus, MDA-SGS can be used for "viral reconstruction" to better understand intrapatient HIV-1 evolution and to determine the clonality and structure of proviruses within expanded clones, including those with drug-resistant mutations. Importantly, we demonstrate that identical sequences observed by standard SGS are not always sufficient to establish proviral clonality., Competing Interests: Competing interest statement: J.W.M. is a consultant to Gilead Sciences, Merck Research Laboratories, Janssen Pharmaceuticals, and AccelevirDx, and a share option holder of Co-Crystal, Inc. B.F.K. and J.A.H. are co-authors on an October 2015 article. The remaining authors have no potential conflicts.
- Published
- 2019
- Full Text
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3. Genome Assembly and Annotation of the Trichoplusia ni Tni-FNL Insect Cell Line Enabled by Long-Read Technologies.
- Author
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Talsania K, Mehta M, Raley C, Kriga Y, Gowda S, Grose C, Drew M, Roberts V, Cheng KT, Burkett S, Oeser S, Stephens R, Soppet D, Chen X, Kumar P, German O, Smirnova T, Hautman C, Shetty J, Tran B, Zhao Y, and Esposito D
- Subjects
- Animals, Cell Line, Contig Mapping, High-Throughput Nucleotide Sequencing, Insect Proteins chemistry, Insect Proteins genetics, Lepidoptera cytology, Protein Domains, Sequence Analysis, DNA, Genome, Insect, Lepidoptera genetics, Molecular Sequence Annotation
- Abstract
Background: Trichoplusia ni derived cell lines are commonly used to enable recombinant protein expression via baculovirus infection to generate materials approved for clinical use and in clinical trials. In order to develop systems biology and genome engineering tools to improve protein expression in this host, we performed de novo genome assembly of the Trichoplusia ni -derived cell line Tni-FNL., Methods: By integration of PacBio single-molecule sequencing, Bionano optical mapping, and 10X Genomics linked-reads data, we have produced a draft genome assembly of Tni-FNL., Results: Our assembly contains 280 scaffolds, with a N50 scaffold size of 2.3 Mb and a total length of 359 Mb. Annotation of the Tni-FNL genome resulted in 14,101 predicted genes and 93.2% of the predicted proteome contained recognizable protein domains. Ortholog searches within the superorder Holometabola provided further evidence of high accuracy and completeness of the Tni-FNL genome assembly., Conclusions: This first draft Tni-FNL genome assembly was enabled by complementary long-read technologies and represents a high-quality, well-annotated genome that provides novel insight into the complexity of this insect cell line and can serve as a reference for future large-scale genome engineering work in this and other similar recombinant protein production hosts., Competing Interests: The authors declare that they have no competing interests.
- Published
- 2019
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4. Three new pancreatic cancer susceptibility signals identified on chromosomes 1q32.1, 5p15.33 and 8q24.21.
- Author
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Zhang M, Wang Z, Obazee O, Jia J, Childs EJ, Hoskins J, Figlioli G, Mocci E, Collins I, Chung CC, Hautman C, Arslan AA, Beane-Freeman L, Bracci PM, Buring J, Duell EJ, Gallinger S, Giles GG, Goodman GE, Goodman PJ, Kamineni A, Kolonel LN, Kulke MH, Malats N, Olson SH, Sesso HD, Visvanathan K, White E, Zheng W, Abnet CC, Albanes D, Andreotti G, Brais L, Bueno-de-Mesquita HB, Basso D, Berndt SI, Boutron-Ruault MC, Bijlsma MF, Brenner H, Burdette L, Campa D, Caporaso NE, Capurso G, Cavestro GM, Cotterchio M, Costello E, Elena J, Boggi U, Gaziano JM, Gazouli M, Giovannucci EL, Goggins M, Gross M, Haiman CA, Hassan M, Helzlsouer KJ, Hu N, Hunter DJ, Iskierka-Jazdzewska E, Jenab M, Kaaks R, Key TJ, Khaw KT, Klein EA, Kogevinas M, Krogh V, Kupcinskas J, Kurtz RC, Landi MT, Landi S, Le Marchand L, Mambrini A, Mannisto S, Milne RL, Neale RE, Oberg AL, Panico S, Patel AV, Peeters PH, Peters U, Pezzilli R, Porta M, Purdue M, Quiros JR, Riboli E, Rothman N, Scarpa A, Scelo G, Shu XO, Silverman DT, Soucek P, Strobel O, Sund M, Małecka-Panas E, Taylor PR, Tavano F, Travis RC, Thornquist M, Tjønneland A, Tobias GS, Trichopoulos D, Vashist Y, Vodicka P, Wactawski-Wende J, Wentzensen N, Yu H, Yu K, Zeleniuch-Jacquotte A, Kooperberg C, Risch HA, Jacobs EJ, Li D, Fuchs C, Hoover R, Hartge P, Chanock SJ, Petersen GM, Stolzenberg-Solomon RS, Wolpin BM, Kraft P, Klein AP, Canzian F, and Amundadottir LT
- Subjects
- Datasets as Topic, Genome-Wide Association Study methods, Genotype, Humans, Polymorphism, Single Nucleotide genetics, Chromosomes, Human, Pair 1 genetics, Chromosomes, Human, Pair 5 genetics, Chromosomes, Human, Pair 8 genetics, Genetic Predisposition to Disease genetics, Pancreatic Neoplasms genetics
- Abstract
Genome-wide association studies (GWAS) have identified common pancreatic cancer susceptibility variants at 13 chromosomal loci in individuals of European descent. To identify new susceptibility variants, we performed imputation based on 1000 Genomes (1000G) Project data and association analysis using 5,107 case and 8,845 control subjects from 27 cohort and case-control studies that participated in the PanScan I-III GWAS. This analysis, in combination with a two-staged replication in an additional 6,076 case and 7,555 control subjects from the PANcreatic Disease ReseArch (PANDoRA) and Pancreatic Cancer Case-Control (PanC4) Consortia uncovered 3 new pancreatic cancer risk signals marked by single nucleotide polymorphisms (SNPs) rs2816938 at chromosome 1q32.1 (per allele odds ratio (OR) = 1.20, P = 4.88x10 -15), rs10094872 at 8q24.21 (OR = 1.15, P = 3.22x10 -9) and rs35226131 at 5p15.33 (OR = 0.71, P = 1.70x10 -8). These SNPs represent independent risk variants at previously identified pancreatic cancer risk loci on chr1q32.1 ( NR5A2), chr8q24.21 ( MYC) and chr5p15.33 ( CLPTM1L- TERT) as per analyses conditioned on previously reported susceptibility variants. We assessed expression of candidate genes at the three risk loci in histologically normal ( n = 10) and tumor ( n = 8) derived pancreatic tissue samples and observed a marked reduction of NR5A2 expression (chr1q32.1) in the tumors (fold change -7.6, P = 5.7x10 -8). This finding was validated in a second set of paired ( n = 20) histologically normal and tumor derived pancreatic tissue samples (average fold change for three NR5A2 isoforms -31.3 to -95.7, P = 7.5x10 -4-2.0x10 -3). Our study has identified new susceptibility variants independently conferring pancreatic cancer risk that merit functional follow-up to identify target genes and explain the underlying biology.
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- 2016
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5. Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome.
- Author
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Machiela MJ, Zhou W, Karlins E, Sampson JN, Freedman ND, Yang Q, Hicks B, Dagnall C, Hautman C, Jacobs KB, Abnet CC, Aldrich MC, Amos C, Amundadottir LT, Arslan AA, Beane-Freeman LE, Berndt SI, Black A, Blot WJ, Bock CH, Bracci PM, Brinton LA, Bueno-de-Mesquita HB, Burdett L, Buring JE, Butler MA, Canzian F, Carreón T, Chaffee KG, Chang IS, Chatterjee N, Chen C, Chen C, Chen K, Chung CC, Cook LS, Crous Bou M, Cullen M, Davis FG, De Vivo I, Ding T, Doherty J, Duell EJ, Epstein CG, Fan JH, Figueroa JD, Fraumeni JF, Friedenreich CM, Fuchs CS, Gallinger S, Gao YT, Gapstur SM, Garcia-Closas M, Gaudet MM, Gaziano JM, Giles GG, Gillanders EM, Giovannucci EL, Goldin L, Goldstein AM, Haiman CA, Hallmans G, Hankinson SE, Harris CC, Henriksson R, Holly EA, Hong YC, Hoover RN, Hsiung CA, Hu N, Hu W, Hunter DJ, Hutchinson A, Jenab M, Johansen C, Khaw KT, Kim HN, Kim YH, Kim YT, Klein AP, Klein R, Koh WP, Kolonel LN, Kooperberg C, Kraft P, Krogh V, Kurtz RC, LaCroix A, Lan Q, Landi MT, Marchand LL, Li D, Liang X, Liao LM, Lin D, Liu J, Lissowska J, Lu L, Magliocco AM, Malats N, Matsuo K, McNeill LH, McWilliams RR, Melin BS, Mirabello L, Moore L, Olson SH, Orlow I, Park JY, Patiño-Garcia A, Peplonska B, Peters U, Petersen GM, Pooler L, Prescott J, Prokunina-Olsson L, Purdue MP, Qiao YL, Rajaraman P, Real FX, Riboli E, Risch HA, Rodriguez-Santiago B, Ruder AM, Savage SA, Schumacher F, Schwartz AG, Schwartz KL, Seow A, Wendy Setiawan V, Severi G, Shen H, Sheng X, Shin MH, Shu XO, Silverman DT, Spitz MR, Stevens VL, Stolzenberg-Solomon R, Stram D, Tang ZZ, Taylor PR, Teras LR, Tobias GS, Van Den Berg D, Visvanathan K, Wacholder S, Wang JC, Wang Z, Wentzensen N, Wheeler W, White E, Wiencke JK, Wolpin BM, Wong MP, Wu C, Wu T, Wu X, Wu YL, Wunder JS, Xia L, Yang HP, Yang PC, Yu K, Zanetti KA, Zeleniuch-Jacquotte A, Zheng W, Zhou B, Ziegler RG, Perez-Jurado LA, Caporaso NE, Rothman N, Tucker M, Dean MC, Yeager M, and Chanock SJ
- Subjects
- DNA Methylation genetics, Female, Humans, Male, Polymerase Chain Reaction, Reproducibility of Results, Aging genetics, Chromosomes, Human, X genetics, Mosaicism, X Chromosome Inactivation genetics
- Abstract
To investigate large structural clonal mosaicism of chromosome X, we analysed the SNP microarray intensity data of 38,303 women from cancer genome-wide association studies (20,878 cases and 17,425 controls) and detected 124 mosaic X events >2 Mb in 97 (0.25%) women. Here we show rates for X-chromosome mosaicism are four times higher than mean autosomal rates; X mosaic events more often include the entire chromosome and participants with X events more likely harbour autosomal mosaic events. X mosaicism frequency increases with age (0.11% in 50-year olds; 0.45% in 75-year olds), as reported for Y and autosomes. Methylation array analyses of 33 women with X mosaicism indicate events preferentially involve the inactive X chromosome. Our results provide further evidence that the sex chromosomes undergo mosaic events more frequently than autosomes, which could have implications for understanding the underlying mechanisms of mosaic events and their possible contribution to risk for chronic diseases.
- Published
- 2016
- Full Text
- View/download PDF
6. Imputation and subset-based association analysis across different cancer types identifies multiple independent risk loci in the TERT-CLPTM1L region on chromosome 5p15.33.
- Author
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Wang Z, Zhu B, Zhang M, Parikh H, Jia J, Chung CC, Sampson JN, Hoskins JW, Hutchinson A, Burdette L, Ibrahim A, Hautman C, Raj PS, Abnet CC, Adjei AA, Ahlbom A, Albanes D, Allen NE, Ambrosone CB, Aldrich M, Amiano P, Amos C, Andersson U, Andriole G Jr, Andrulis IL, Arici C, Arslan AA, Austin MA, Baris D, Barkauskas DA, Bassig BA, Beane Freeman LE, Berg CD, Berndt SI, Bertazzi PA, Biritwum RB, Black A, Blot W, Boeing H, Boffetta P, Bolton K, Boutron-Ruault MC, Bracci PM, Brennan P, Brinton LA, Brotzman M, Bueno-de-Mesquita HB, Buring JE, Butler MA, Cai Q, Cancel-Tassin G, Canzian F, Cao G, Caporaso NE, Carrato A, Carreon T, Carta A, Chang GC, Chang IS, Chang-Claude J, Che X, Chen CJ, Chen CY, Chen CH, Chen C, Chen KY, Chen YM, Chokkalingam AP, Chu LW, Clavel-Chapelon F, Colditz GA, Colt JS, Conti D, Cook MB, Cortessis VK, Crawford ED, Cussenot O, Davis FG, De Vivo I, Deng X, Ding T, Dinney CP, Di Stefano AL, Diver WR, Duell EJ, Elena JW, Fan JH, Feigelson HS, Feychting M, Figueroa JD, Flanagan AM, Fraumeni JF Jr, Freedman ND, Fridley BL, Fuchs CS, Gago-Dominguez M, Gallinger S, Gao YT, Gapstur SM, Garcia-Closas M, Garcia-Closas R, Gastier-Foster JM, Gaziano JM, Gerhard DS, Giffen CA, Giles GG, Gillanders EM, Giovannucci EL, Goggins M, Gokgoz N, Goldstein AM, Gonzalez C, Gorlick R, Greene MH, Gross M, Grossman HB, Grubb R 3rd, Gu J, Guan P, Haiman CA, Hallmans G, Hankinson SE, Harris CC, Hartge P, Hattinger C, Hayes RB, He Q, Helman L, Henderson BE, Henriksson R, Hoffman-Bolton J, Hohensee C, Holly EA, Hong YC, Hoover RN, Hosgood HD 3rd, Hsiao CF, Hsing AW, Hsiung CA, Hu N, Hu W, Hu Z, Huang MS, Hunter DJ, Inskip PD, Ito H, Jacobs EJ, Jacobs KB, Jenab M, Ji BT, Johansen C, Johansson M, Johnson A, Kaaks R, Kamat AM, Kamineni A, Karagas M, Khanna C, Khaw KT, Kim C, Kim IS, Kim JH, Kim YH, Kim YC, Kim YT, Kang CH, Jung YJ, Kitahara CM, Klein AP, Klein R, Kogevinas M, Koh WP, Kohno T, Kolonel LN, Kooperberg C, Kratz CP, Krogh V, Kunitoh H, Kurtz RC, Kurucu N, Lan Q, Lathrop M, Lau CC, Lecanda F, Lee KM, Lee MP, Le Marchand L, Lerner SP, Li D, Liao LM, Lim WY, Lin D, Lin J, Lindstrom S, Linet MS, Lissowska J, Liu J, Ljungberg B, Lloreta J, Lu D, Ma J, Malats N, Mannisto S, Marina N, Mastrangelo G, Matsuo K, McGlynn KA, McKean-Cowdin R, McNeill LH, McWilliams RR, Melin BS, Meltzer PS, Mensah JE, Miao X, Michaud DS, Mondul AM, Moore LE, Muir K, Niwa S, Olson SH, Orr N, Panico S, Park JY, Patel AV, Patino-Garcia A, Pavanello S, Peeters PH, Peplonska B, Peters U, Petersen GM, Picci P, Pike MC, Porru S, Prescott J, Pu X, Purdue MP, Qiao YL, Rajaraman P, Riboli E, Risch HA, Rodabough RJ, Rothman N, Ruder AM, Ryu JS, Sanson M, Schned A, Schumacher FR, Schwartz AG, Schwartz KL, Schwenn M, Scotlandi K, Seow A, Serra C, Serra M, Sesso HD, Severi G, Shen H, Shen M, Shete S, Shiraishi K, Shu XO, Siddiq A, Sierrasesumaga L, Sierri S, Loon Sihoe AD, Silverman DT, Simon M, Southey MC, Spector L, Spitz M, Stampfer M, Stattin P, Stern MC, Stevens VL, Stolzenberg-Solomon RZ, Stram DO, Strom SS, Su WC, Sund M, Sung SW, Swerdlow A, Tan W, Tanaka H, Tang W, Tang ZZ, Tardon A, Tay E, Taylor PR, Tettey Y, Thomas DM, Tirabosco R, Tjonneland A, Tobias GS, Toro JR, Travis RC, Trichopoulos D, Troisi R, Truelove A, Tsai YH, Tucker MA, Tumino R, Van Den Berg D, Van Den Eeden SK, Vermeulen R, Vineis P, Visvanathan K, Vogel U, Wang C, Wang C, Wang J, Wang SS, Weiderpass E, Weinstein SJ, Wentzensen N, Wheeler W, White E, Wiencke JK, Wolk A, Wolpin BM, Wong MP, Wrensch M, Wu C, Wu T, Wu X, Wu YL, Wunder JS, Xiang YB, Xu J, Yang HP, Yang PC, Yatabe Y, Ye Y, Yeboah ED, Yin Z, Ying C, Yu CJ, Yu K, Yuan JM, Zanetti KA, Zeleniuch-Jacquotte A, Zheng W, Zhou B, Mirabello L, Savage SA, Kraft P, Chanock SJ, Yeager M, Landi MT, Shi J, Chatterjee N, and Amundadottir LT
- Subjects
- Alleles, Computational Biology, DNA Methylation, Epigenesis, Genetic, Female, Gene Frequency, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Neoplasms pathology, Odds Ratio, Polymorphism, Single Nucleotide, Risk, Chromosomes, Human, Pair 5 chemistry, Gene Expression Regulation, Neoplastic, Genetic Loci, Membrane Proteins genetics, Neoplasm Proteins genetics, Neoplasms genetics, Telomerase genetics
- Abstract
Genome-wide association studies (GWAS) have mapped risk alleles for at least 10 distinct cancers to a small region of 63 000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis. To investigate further the genetic architecture of common susceptibility alleles in this region, we conducted an agnostic subset-based meta-analysis (association analysis based on subsets) across six distinct cancers in 34 248 cases and 45 036 controls. Based on sequential conditional analysis, we identified as many as six independent risk loci marked by common single-nucleotide polymorphisms: five in the TERT gene (Region 1: rs7726159, P = 2.10 × 10(-39); Region 3: rs2853677, P = 3.30 × 10(-36) and PConditional = 2.36 × 10(-8); Region 4: rs2736098, P = 3.87 × 10(-12) and PConditional = 5.19 × 10(-6), Region 5: rs13172201, P = 0.041 and PConditional = 2.04 × 10(-6); and Region 6: rs10069690, P = 7.49 × 10(-15) and PConditional = 5.35 × 10(-7)) and one in the neighboring CLPTM1L gene (Region 2: rs451360; P = 1.90 × 10(-18) and PConditional = 7.06 × 10(-16)). Between three and five cancers mapped to each independent locus with both risk-enhancing and protective effects. Allele-specific effects on DNA methylation were seen for a subset of risk loci, indicating that methylation and subsequent effects on gene expression may contribute to the biology of risk variants on 5p15.33. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, to an extent not previously observed in other cancer susceptibility loci., (Published by Oxford University Press 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.)
- Published
- 2014
- Full Text
- View/download PDF
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